The Centers for Disease Control and Prevention (CDC) reported that in 2010 approximately 40.5% of men aged 20-74 in the US were obese or morbidly obese while the rate of morbidly obese patients was 4.5%. The obesity rate is still rapidly growing. This demographic is mirrored in the radiation oncology patient population. The need for obese specific tools, such as heavier couch weight limits and large-bore CT simulators, are needed in part as a response to this changing demographic. In addition, CT simulation scans, the acquisition of a CT scan image for radiation treatment planning, is also impacted by patient obesity.
A CT simulation scan is used to define tumor and normal organ anatomy by segmenting the tumors and organs manually or by using commercial available semi-automated and automated techniques for segmenting tumors and organs. A physician develops a prescription that defines the tumor dose and dose limits to critical organs. The segmented targets for the tumors and organs are used to define the radiation beams and beam fluences in a treatment plan that is compared against the prescription to determine its clinical acceptability. Once approved, the plan parameters are transferred to a linear accelerator for delivery of treatment doses of radiation to the patient.
Accurate tumor volume (contour) and critical organ segmentations are critical for maximizing tumor conformality. Tumor contour and organ segmentation primarily depend on tumor and critical structure CT conspicuity, interpretation of radiological anatomy, and understanding of the potential areas of tumor involvement based on tumor biology with a central assumption that CT-based target segmentation provides an accurate patient anatomy description. CT simulation scanning is the standard of care in radiation therapy for the simulation of prostate cancer patients, and will likely remain so for the foreseeable future. CT simulation scanning is the standard of care because of its availability, large bore size, fast acquisition, high geometrical accuracy, and direct connections to electron density used for radiation dose calculations. CT simulation scans are used to provide quantitative target and structure segmentation for accurate radiation treatment planning.
Conventionally, CT simulation scans and scanning equipment are designed based on the underlying assumptions used to design the CT diagnostic protocols. Such design assumptions, however, may not match those in the radiation oncology workflow, especially for obese prostate cancer patients. At present, default CT simulation protocols for obese prostate cancer patients are revised by increasing the amperage (mAs) of the x-ray tube. The limitation of this approach is that, while increased mAs have an impact on image quality, increased amperage, as shown in FIG. 2 may be insufficient for some patients, especially obese patients. FIG. 2 shows examples of clinical treatment planning CT scans from obese (a) and thin (b) prostate cancer patients having lateral pelvis diameters of 60 centimeters (cm) and 33 cm, respectively. The image of the thin patient (FIG. 2b) clearly shows the prostate and bladder, while the image of the obese patient (FIG. 2a) contains high noise levels and residual photon starvation artifacts, degrading the image quality to the extent that the prostate and bladder are virtually hidden. Each patient had very different volume CT dose index (CTDIvol), a measure of absorbed radiation. The obese patient (FIG. 2a) had a CTDIvol value of 67.2 milligrays (mGy), and the thin patient (FIG. 2b) had a CTDIvol value of 18.2 mGy. In spite of the increased x-ray fluence (67.2 mGy v. 18.2 mGy), the obese patient image still suffered from photon starvation. In the case of the obese patient, the therapists had increased the mAs to the maximum available by the clinical protocol.
CT simulation scanning, the acquisition of a CT scan for radiation treatment planning, is the first step in the radiation therapy workflow. CT simulation images are used to define tumor and normal organ anatomy by manual techniques or increasingly by use of commercial semi-automated or automated techniques. As previously stated, accurate tumor volume and normal organ segmentations are critical for maximizing dose conformality. Accurate segmentation relies on tumor and critical structure CT conspicuity, interpretation of radiological anatomy, and understanding of the potential areas of tumor involvement based on tumor biology with a main assumption that target segmentation based on CT simulation scans provides an accurate patient anatomy description. Diagnostic CT scanning protocols are driven by subjective image quality and radiation dose minimization as defined by the “as low as reasonably achievable” (ALARA) principle. However, one goal of radiation oncology CT simulation scans is to provide quantitative target and critical structure segmentation, which plays a critical role for accurate radiation treatment planning. In addition, the treatment-related normal organ dose received by most radiation oncology patients, even far from the tumor, greatly exceeds the dose from a CT simulation scan. Therefore, radiation oncology patients, especially obese patients, should not be subject to the same dose constraints as diagnostic imaging patients when those constraints compromise the accuracy of tumor and normal tissue segmentation. Up to now, methods for objectively optimizing CT simulation protocols to take into account radiation dose, patient size, and treatment planning requirements have not been developed.
The optimal CT simulation protocol is the one that delivers the minimum dose required to provide a CT simulation scan that yields accurate contours. Accurate treatment plans depend on accurate contours in order to conform the dose to actual tumor and normal organ positions. Previous diagnostic CT imaging studies have shown that a frequently employed method to manage CT image quality and radiation dose is to adjust the x-ray tube current using patient size or weight-based protocols. Also, the tradeoff between image noise and contrast enhancement determined the clinically optimal x-ray tube potential that yields the best image quality at the lowest radiation dose for a given patient size and clinical application. As shown in FIG. 1(a), low dose protocols yield lower image quality and cause inaccurate target contouring and poor treatment plans, which do not adequately cover the tumor or avoid the critical structures. For sufficiently high dose protocols, the segmentation (or contouring) is accurate such that further increasing the technique only reduces image noise but has no impact on contouring and negligible impact on the resulting treatment plan and therapy dose distribution. Hence, for a given patient size, an optimal CT simulation protocol exists that delivers the minimum dose while providing a CT image data set that yields accurate contours, defined as contours that yield accurate treatment plans, conforming the dose to the actual tumor and normal organ positions.